Kgaphola, Motsoko JRamoelo, AbelOdindi, JMwenge Kahinda, Jean-MarcSeetal, Ashwin R2023-05-082023-05-082023-03Kgaphola, M.J., Ramoelo, A., Odindi, J., Mwenge Kahinda, J. & Seetal, R.A. 2023. Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality. <i>Applied Sciences, 13(6).</i> http://hdl.handle.net/10204/127612076-3417https://doi.org/10.3390/app13063644http://hdl.handle.net/10204/12761Land degradation (LD) is a global issue that affects sustainability and livelihoods of approximately 1.5 billion people, especially in arid/semi-arid regions. Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate sustainable land management interventions. Therefore, using vegetation as a proxy for LD, this study aimed to distinguish anthropogenic from rainfall-driven LD in the Greater Sekhukhune District Municipality from 1990 to 2019. It is widely established that rainfall highly correlates with vegetation productivity. A linear regression was performed between the Normalized Difference Vegetation Index (NDVI) and rainfall. The human-induced LD was then distinguished from that of rainfall using the spatial residual trend (RESTREND) method and the Mann–Kendall (MK) trend. RESTREND results showed that 11.59% of the district was degraded due to human activities such as overgrazing and injudicious rangeland management. While about 41.41% was degraded due to seasonal rainfall variability and an increasing frequency of droughts. Climate variability affected vegetation cover and contributed to different forms of soil erosion and gully formation. These findings provide relevant spatial information on rainfall or human-induced LD, which is useful for policy formulation and the design of LD mitigation measures in semi-arid regions.FulltextenLand degradationLand Use and Land Cover ChangeMann-Kendall trendNormalized Difference Vegetation IndexNDVIRainfallResidual trendRESTRENDArticleKgaphola, M. J., Ramoelo, A., Odindi, J., Mwenge Kahinda, J., & Seetal, R. A. (2023). Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality. <i>Applied Sciences, 13(6)</i>, http://hdl.handle.net/10204/12761Kgaphola, Motsoko J, A Ramoelo, J Odindi, Jean-Marc Mwenge Kahinda, and R Ashwin Seetal "Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality." <i>Applied Sciences, 13(6)</i> (2023) http://hdl.handle.net/10204/12761Kgaphola MJ, Ramoelo A, Odindi J, Mwenge Kahinda J, Seetal RA. Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality. Applied Sciences, 13(6). 2023; http://hdl.handle.net/10204/12761.TY - Article AU - Kgaphola, Motsoko J AU - Ramoelo, A AU - Odindi, J AU - Mwenge Kahinda, Jean-Marc AU - Seetal, R Ashwin AB - Land degradation (LD) is a global issue that affects sustainability and livelihoods of approximately 1.5 billion people, especially in arid/semi-arid regions. Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate sustainable land management interventions. Therefore, using vegetation as a proxy for LD, this study aimed to distinguish anthropogenic from rainfall-driven LD in the Greater Sekhukhune District Municipality from 1990 to 2019. It is widely established that rainfall highly correlates with vegetation productivity. A linear regression was performed between the Normalized Difference Vegetation Index (NDVI) and rainfall. The human-induced LD was then distinguished from that of rainfall using the spatial residual trend (RESTREND) method and the Mann–Kendall (MK) trend. RESTREND results showed that 11.59% of the district was degraded due to human activities such as overgrazing and injudicious rangeland management. While about 41.41% was degraded due to seasonal rainfall variability and an increasing frequency of droughts. Climate variability affected vegetation cover and contributed to different forms of soil erosion and gully formation. These findings provide relevant spatial information on rainfall or human-induced LD, which is useful for policy formulation and the design of LD mitigation measures in semi-arid regions. DA - 2023-03 DB - ResearchSpace DP - CSIR J1 - Applied Sciences, 13(6) KW - Land degradation KW - Land Use and Land Cover Change KW - Mann-Kendall trend KW - Normalized Difference Vegetation Index KW - NDVI KW - Rainfall KW - Residual trend KW - RESTREND LK - https://researchspace.csir.co.za PY - 2023 SM - 2076-3417 T1 - Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality TI - Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality UR - http://hdl.handle.net/10204/12761 ER -2637426672